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Record W2082608910 · doi:10.1177/0920203x06070038

From the Mountains and the Fields

2006· article· en· W2082608910 on OpenAlexaff
Alan Smart, Li Zhang

Bibliographic record

VenueChina Information · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsUrbanizationChinaSociologyUrban anthropologyLatin AmericansGentrificationCapital (architecture)Economic geographyPolitical scienceEconomic growthUrban planningRegional scienceGeographyUrban density

Abstract

fetched live from OpenAlex

This article critically reviews important developments in the anthropology of urban China. Although its primary focus is on works by China anthropologists, it addresses the interdisciplinary challenge and the increasingly ambiguous boundary between the “rural” and the “urban”. More specifically, the article analyzes major theoretical and pragmatic issues addressed by anthropologists in the following seven thematic areas: minority urbanization; urban economies and the influence of global capital; health; kinship and gender; migration; urban space and community; consumption and popular culture. Each section seeks to juxtapose competing arguments made by scholars and analyzes the larger implications of their findings. It further suggests three research directions that the anthropology of urban China could take in the future—a greater interdisciplinary approach to incorporate insights from other related fields, a larger comparative perspective that situates postreform urban China in relation to other formerly socialist countries and other developing cities in Latin America and Africa, and finally greater capabilities for integrating different levels of analysis by rescaling the levels at which social activities and institutions operate today.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.009
Scholarly communication0.0040.003
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.212
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations21
Published2006
Admission routes1
Has abstractyes

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